class_docstr: Evalutes note-based negative likelihood.
code: def _draw_ordering(self, tt, dd):
      o = np.arange(tt * dd, dtype=np.int32)
      if not self.chronological:
          np.random.shuffle(o)
      ts, ds = np.unravel_index(o.T, shape=(tt, dd))
      return ts, ds
  
imports: import time
  from magenta.models.coconet import lib_tfutil
  from magenta.models.coconet import lib_util
  import numpy
  from scipy.misc import logsumexp
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the NoteEvaluator obj's underlying member method code with example usage: obj._draw_ordering(tt, dd) and returns: ts,  ds